Update on "Let torch.sign support complex types"

The rule follows those of NumPy: https://numpy.org/doc/stable/reference/generated/numpy.sign.html

[ghstack-poisoned]

.circleci/cimodel/data/pytorch_build_data.py

@@ -28,22 +28,30 @@
         ]),
         ("cuda", [
             ("9.2", [
-                X("3.6"),
                 ("3.6", [
-                    ("cuda_gcc_override", [X("gcc5.4")])
+                    X(True),
+                    ("cuda_gcc_override", [
+                        ("gcc5.4", [
+                            ('build_only', [XImportant(True)]),
+                        ]),
+                    ]),
                 ])
             ]),
-            ("10.1", [X("3.6")]),
+            ("10.1", [
+                ("3.6", [
+                    ('build_only', [X(True)]),
+                ]),
+            ]),
             ("10.2", [
-                XImportant("3.6"),
                 ("3.6", [
-                    ("libtorch", [XImportant(True)])
+                    ("important", [X(True)]),
+                    ("libtorch", [X(True)]),
                 ]),
             ]),
             ("11.0", [
-                X("3.8"),
                 ("3.8", [
-                    ("libtorch", [X(True)])
+                    X(True),
+                    ("libtorch", [XImportant(True)])
                 ]),
             ]),
         ]),
@@ -200,15 +208,15 @@ def init2(self, node_name):
         self.props["cuda_gcc_override"] = node_name
 
     def child_constructor(self):
-        return ImportantConfigNode
+        return ExperimentalFeatureConfigNode
 
 class BuildOnlyConfigNode(TreeConfigNode):
 
     def init2(self, node_name):
         self.props["build_only"] = node_name
 
     def child_constructor(self):
-        return ImportantConfigNode
+        return ExperimentalFeatureConfigNode
 
 
 class ImportantConfigNode(TreeConfigNode):

.circleci/config.yml

@@ -5721,28 +5721,8 @@ workflows:
           name: pytorch_linux_xenial_cuda9_2_cudnn7_py3_gcc5_4_build
           requires:
             - "docker-pytorch-linux-xenial-cuda9.2-cudnn7-py3-gcc5.4"
-          filters:
-            branches:
-              only:
-                - master
-                - /ci-all\/.*/
-                - /release\/.*/
           build_environment: "pytorch-linux-xenial-cuda9.2-cudnn7-py3-gcc5.4-build"
           docker_image: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-cuda9.2-cudnn7-py3-gcc5.4"
-      - pytorch_linux_test:
-          name: pytorch_linux_xenial_cuda9_2_cudnn7_py3_gcc5_4_test
-          requires:
-            - pytorch_linux_xenial_cuda9_2_cudnn7_py3_gcc5_4_build
-          filters:
-            branches:
-              only:
-                - master
-                - /ci-all\/.*/
-                - /release\/.*/
-          build_environment: "pytorch-linux-xenial-cuda9.2-cudnn7-py3-gcc5.4-test"
-          docker_image: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-cuda9.2-cudnn7-py3-gcc5.4"
-          use_cuda_docker_runtime: "1"
-          resource_class: gpu.medium
       - pytorch_linux_build:
           name: pytorch_linux_xenial_cuda10_1_cudnn7_py3_gcc7_build
           requires:
@@ -5755,20 +5735,6 @@ workflows:
                 - /release\/.*/
           build_environment: "pytorch-linux-xenial-cuda10.1-cudnn7-py3-gcc7-build"
           docker_image: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-cuda10.1-cudnn7-py3-gcc7"
-      - pytorch_linux_test:
-          name: pytorch_linux_xenial_cuda10_1_cudnn7_py3_gcc7_test
-          requires:
-            - pytorch_linux_xenial_cuda10_1_cudnn7_py3_gcc7_build
-          filters:
-            branches:
-              only:
-                - master
-                - /ci-all\/.*/
-                - /release\/.*/
-          build_environment: "pytorch-linux-xenial-cuda10.1-cudnn7-py3-gcc7-test"
-          docker_image: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-cuda10.1-cudnn7-py3-gcc7"
-          use_cuda_docker_runtime: "1"
-          resource_class: gpu.medium
       - pytorch_linux_test:
           name: pytorch_linux_xenial_cuda10_1_cudnn7_py3_multigpu_test
           requires:
@@ -5841,12 +5807,24 @@ workflows:
           name: pytorch_libtorch_linux_xenial_cuda10_2_cudnn7_py3_gcc7_build
           requires:
             - "docker-pytorch-linux-xenial-cuda10.2-cudnn7-py3-gcc7"
+          filters:
+            branches:
+              only:
+                - master
+                - /ci-all\/.*/
+                - /release\/.*/
           build_environment: "pytorch-libtorch-linux-xenial-cuda10.2-cudnn7-py3-gcc7-build"
           docker_image: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-cuda10.2-cudnn7-py3-gcc7"
       - pytorch_linux_test:
           name: pytorch_libtorch_linux_xenial_cuda10_2_cudnn7_py3_gcc7_test
           requires:
             - pytorch_libtorch_linux_xenial_cuda10_2_cudnn7_py3_gcc7_build
+          filters:
+            branches:
+              only:
+                - master
+                - /ci-all\/.*/
+                - /release\/.*/
           build_environment: "pytorch-libtorch-linux-xenial-cuda10.2-cudnn7-py3-gcc7-test"
           docker_image: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-cuda10.2-cudnn7-py3-gcc7"
           use_cuda_docker_runtime: "1"
@@ -5881,24 +5859,12 @@ workflows:
           name: pytorch_libtorch_linux_xenial_cuda11_0_cudnn8_py3_gcc7_build
           requires:
             - "docker-pytorch-linux-xenial-cuda11.0-cudnn8-py3-gcc7"
-          filters:
-            branches:
-              only:
-                - master
-                - /ci-all\/.*/
-                - /release\/.*/
           build_environment: "pytorch-libtorch-linux-xenial-cuda11.0-cudnn8-py3-gcc7-build"
           docker_image: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-cuda11.0-cudnn8-py3-gcc7"
       - pytorch_linux_test:
           name: pytorch_libtorch_linux_xenial_cuda11_0_cudnn8_py3_gcc7_test
           requires:
             - pytorch_libtorch_linux_xenial_cuda11_0_cudnn8_py3_gcc7_build
-          filters:
-            branches:
-              only:
-                - master
-                - /ci-all\/.*/
-                - /release\/.*/
           build_environment: "pytorch-libtorch-linux-xenial-cuda11.0-cudnn8-py3-gcc7-test"
           docker_image: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-cuda11.0-cudnn8-py3-gcc7"
           use_cuda_docker_runtime: "1"

.jenkins/pytorch/test.sh

@@ -64,8 +64,9 @@ fi
 if [[ "$BUILD_ENVIRONMENT" != *ppc64le* ]] && [[ "$BUILD_ENVIRONMENT" != *-bazel-* ]] ; then
   # JIT C++ extensions require ninja.
   pip_install --user ninja
-  # ninja is installed in /var/lib/jenkins/.local/bin
-  export PATH="/var/lib/jenkins/.local/bin:$PATH"
+  # ninja is installed in $HOME/.local/bin, e.g., /var/lib/jenkins/.local/bin for CI user jenkins
+  # but this script should be runnable by any user, including root
+  export PATH="$HOME/.local/bin:$PATH"
 
   # TODO: Please move this to Docker
   # The version is fixed to avoid flakiness: https://github.com/pytorch/pytorch/issues/31136

aten/src/ATen/native/cudnn/RNN.cpp

@@ -684,7 +684,7 @@ namespace cudnn_rnn {
       }
     }
 
-    return {weight_buf, params_arr};
+    return std::make_tuple(weight_buf, params_arr);
   }
 
 } // namespace cudnn_rnn

test/test_torch.py

@@ -5985,8 +5985,6 @@ def test_complex_assert_raises(self, device):
                 self.assertRaises(RuntimeError,
                                   lambda: zeros.index_add(0, torch.arange(0, size[0], dtype=torch.long, device=device), tensor))
 
-            self.assertRaises(RuntimeError, lambda: torch.sign(torch.tensor([4j], device=device, dtype=dtype)))
-
             a = torch.rand((2, 2), dtype=dtype, device=device)
             b = torch.rand((2, 2), dtype=dtype, device=device)
             c = torch.rand((2, 2), dtype=dtype, device=device)